Minimizing and exploiting leakage in VLSI

Power consumption of VLSI (Very Large Scale Integrated) circuits has been growing at an alarmingly rapid rate. This increase in power consumption, coupled with the increasing demand for portable/hand-held electronics, has made power consumption a dominant concern in the design of VLSI circuits today. Traditionally dynamic (switching) power has dominated the total power consumption of VLSI circuits. However, due to process scaling trends, leakage power has now become a major component of the total power consumption in VLSI circuits. This dissertation explores techniques to reduce leakage, as well as techniques to exploit leakage currents through the use of sub-threshold circuits. This dissertation consists of two studies. In the first study, techniques to reduce leakage are presented. These include a low leakage ASIC design methodology that uses high VT sleep transistors selectively, a methodology that combines input vector control and circuit modification, and a scheme to find the optimum reverse body bias voltage to minimize leakage. As the minimum feature size of VLSI fabrication processes continues to shrink with each successive process generation (along with the value of supply voltage and therefore the threshold voltage of the devices), leakage currents increase exponentially. Leakage currents are hence seen as a necessary evil in traditional VLSI design methodologies. We present an approach to turn this problem into an opportunity. In the second study in this dissertation, we attempt to exploit leakage currents to perform computation. We use sub-threshold digital circuits and come up with ways to get around some of the pitfalls associated with sub-threshold circuit design. These include a technique that uses body biasing adaptively to compensate for Process, Voltage and Temperature (PVT) variations, a design approach that uses asynchronous micro-pipelined Network of Programmable Logic Arrays (NPLAs) to help improve the throughput of sub-threshold designs, and a method to find the optimum supply voltage that minimizes energy consumption in a circuit

Cost-Efficient Soft-Error Resiliency for ASIP-based Embedded Systems

Recent decades have witnessed the rapid growth of embedded systems. At present, embedded systems are widely applied in a broad range of critical applications including automotive electronics, telecommunication, healthcare, industrial electronics, consumer electronics military and aerospace. Human society will continue to be greatly transformed by the pervasive deployment of embedded systems. Consequently, substantial amount of efforts from both industry and academic communities have contributed to the research and development of embedded systems. Application-specific instruction-set processor (ASIP) is one of the key advances in embedded processor technology, and a crucial component in some embedded systems. Soft errors have been directly observed since the 1970s. As devices scale, the exponential increase in the integration of computing systems occurs, which leads to correspondingly decrease in the reliability of computing systems. Today, major research forums state that soft errors are one of the major design technology challenges at and beyond the 22 nm technology node. Therefore, a large number of soft-error solutions, including error detection and recovery, have been proposed from differing perspectives. Nonetheless, most of the existing solutions are designed for general or high-performance systems which are different to embedded systems. For embedded systems, the soft-error solutions must be cost-efficient, which requires the tailoring of the processor architecture with respect to the feature of the target application. This thesis embodies a series of explorations for cost-efficient soft-error solutions for ASIP-based embedded systems. In this exploration, five major solutions are proposed. The first proposed solution realizes checkpoint recovery in ASIPs. By generating customized instructions, ASIP-implemented checkpoint recovery can perform at a finer granularity than what was previously possible. The fault-free performance overhead of this solution is only 1.45% on average. The recovery delay is only 62 cycles at the worst case. The area and leakage power overheads are 44.4% and 45.6% on average. The second solution explores utilizing two primitive error recovery techniques jointly. This solution includes three application-specific optimization methodologies. This solution generates the optimized error-resilient ASIPs, based on the characteristics of primitive error recovery techniques, static reliability analysis and design constraints. The resultant ASIP can be configured to perform at runtime according to the optimized recovery scheme. This solution can strategically enhance cost-efficiency for error recovery. In order to guarantee cost-efficiency in unpredictable runtime situations, the third solution explores runtime adaptation for error recovery. This solution aims to budget and adapt the error recovery operations, so as to spend the resources intelligently and to tolerate adverse influences of runtime variations. The resultant ASIP can make runtime decisions to determine the activation of spatial and temporal redundancies, according to the runtime situations. At the best case, this solution can achieve almost 50x reliability gain over the state of the art solutions. Given the increasing demand for multi-core computing systems, the last two proposed solutions target error recovery in multi-core ASIPs. The first solution of these two explores ASIP-implemented fine-grained process migration. This solution is a key infrastructure, which allows cost-efficient task management, for realizing cost-efficient soft-error recovery in multi-core ASIPs. The average time cost is only 289 machine cycles to perform process migration. The last solution explores using dynamic and adaptive mapping to assign heterogeneous recovery operations to the tasks in the multi-core context. This solution allows each individual ASIP-based processing core to dynamically adapt its specific error recovery functionality according to the corresponding task's characteristics, in terms of soft error vulnerability and execution time deadline. This solution can significantly improve the reliability of the system by almost two times, with graceful constraint penalty, in comparison to the state-of-the-art counterparts

Design at the end of the silicon roadmap

Scaling of silicon integrated technology into the deep sub-100 nm space brings with it a number of formidable challenges to the designer. Issues such as design complexity, power dissipation, process variability and reliability are challenging the traditional design methodologies. In this presentation, it is conjectured that the only viable long-term solution to these challenges is to drastically revise the way we do design, and a roadmap of potential solutions is presented. Ultimately, these innovative design solutions will help to pave the way to the post-silicon era